docstr: Parameters
  ----------
  module : torch.nn.Module
      Layer module of pytorch model
  module_bits : int
      Bits width setting for module
docstr_tok: ["Parameters","--","--","--","--","--","module",":","torch.nn.Module","Layer","module","of","pytorch","model","module_bits",":","int","Bits","width","setting","for","module"]
code: def __init__(self, module, module_bits) -> None:
      """
      Parameters
      ----------
      module : torch.nn.Module
          Layer module of pytorch model
      module_bits : int
          Bits width setting for module
      """
      super().__init__()
      self.module = module
      self.module_bits = module_bits
  
file_path: nni/nni/compression/quantization_speedup/frontend_to_onnx.py
imports: import torch
  import onnx
  import onnx.numpy_helper
  from ..utils import set_nested_attr
label_desc: Use image node_id 1 to create a new LayernameModuleWrapper object from inherited base classes: torch.nn with example: obj = LayernameModuleWrapper(module, module_bits)